Responsibilities
Develop and apply mathematical or statistical methods such as multivariate regression to process, analyze, interpret, and summarize data to provide insights into the performance and impact of data science projects
Create presentations and Tableau dashboards to report on user behavior and key KPIs as a result of launching new machine learning features
Administer A/B tests and evaluate the results using statistical methods to compare clickstream, email and order data
Partner with product managers and data scientists to identify new opportunities requiring the use of modern analytical and modeling techniques
Analyze structured and unstructured data to evaluate the validity and opportunity of new projects

Qualifications
BS (MS preferred) degree in a quantitative discipline (e.g., statistics, operations research, econometrics, computer science, applied mathematics, physics, electrical engineering, industrial engineering) or equivalent experience
3+ years experience doing quantitative analysis or statistical modeling
Proven experience influencing product strategy through data-centric presentations (to product, business, and other stakeholders)
Proficiency in SQL and statistical packages (e.g. R). Familiarity with Python would be a plus
Experience processing and manipulating large datasets
Nice to have: Experience in retail/ecommerce data analysis

About Us
Rue Gilt Groupe combines world-class merchandising, technology and marketing to create the most engaging and satisfying online shopping experience available. Each day, 30+ million loyal Members turn to Rue La La and Gilt Groupe for everything from women, men and children’s apparel and accessories to home décor and exclusive experiences. Our approach to retail brings excitement to online shopping in a way that not only strategically supports our brand partners, but also inspires our Members daily.
This Company is an equal opportunity employer, and selects individuals best matched for the job based upon job-related qualifications regardless of race, religion, color, creed, sex, sexual orientation, age, ancestry, national origin, gender identity, genetic information, disability, pregnancy, veteran or military status or any other status or characteristic protected by law.

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